Simple conjugate gradients optimizer. More...

#include <IMP/core/ConjugateGradients.h>

Inheritance diagram for IMP::core::ConjugateGradients:

Public Member Functions
	ConjugateGradients (Model *m=nullptr)

virtual void	do_show (std::ostream &out) const

void	set_gradient_threshold (Float t)
	Set the threshold for the minimum gradient.

void	set_max_change (Float t)
	Limit how far anything can change each time step.

Public Member Functions inherited from IMP::kernel::Optimizer
	Optimizer (Model *m, std::string name="Optimizer %1%")

double	get_last_score () const
	Return the score found in the last evaluate.

Model *	get_model () const
	Get the model being optimized.

ScoringFunction *	get_scoring_function () const
	Return the scoring function that is being used.

bool	get_stop_on_good_score () const

double	optimize (unsigned int max_steps)
	Optimize the model for up to max_steps iterations. More...

void	set_model (Model *m)
	Set the model being optimized. More...

virtual void	set_scoring_function (ScoringFunctionAdaptor sf)

void	set_stop_on_good_score (bool tf)

virtual void	show (std::ostream &out=std::cout) const
	Print info about the optimizer state. More...

void	remove_optimizer_state (OptimizerState *d)

void	remove_optimizer_states (const OptimizerStates &d)

void	set_optimizer_states (const OptimizerStates &ps)

void	set_optimizer_states_order (const OptimizerStates &objs)

unsigned int	add_optimizer_state (OptimizerState *obj)

void	add_optimizer_states (const OptimizerStates &objs)

void	clear_optimizer_states ()

unsigned int	get_number_of_optimizer_states () const

bool	get_has_optimizer_states ()

OptimizerState *	get_optimizer_state (unsigned int i) const

OptimizerStates	get_optimizer_states () const

void	reserve_optimizer_states (unsigned int sz)

Public Member Functions inherited from IMP::base::Object
virtual void	clear_caches ()

virtual IMP::base::VersionInfo	get_version_info () const =0
	Get information about the module and version of the object.

void	set_check_level (CheckLevel l)

void	set_log_level (LogLevel l)
	Set the logging level used in this object. More...

void	set_was_used (bool tf) const

void	show (std::ostream &out=std::cout) const

const std::string &	get_name () const

void	set_name (std::string name)

Additional Inherited Members
Protected Member Functions inherited from IMP::kernel::Optimizer
virtual double	do_optimize (unsigned int ns)=0
	override this function to do actual optimization

void	update_states () const
	Update optimizer states, should be called at each successful step. More...

double	width (FloatKey k) const

FloatIndexes	get_optimized_attributes () const

void	set_value (FloatIndex fi, double v) const

Float	get_value (FloatIndex fi) const

Float	get_derivative (FloatIndex fi) const

void	set_scaled_value (FloatIndex fi, Float v) const

double	get_scaled_value (FloatIndex fi) const

double	get_scaled_derivative (FloatIndex fi) const

void	clear_range_cache ()
	Clear the cache of range information. Do this at the start of optimization.

Related Functions inherited from IMP::kernel::Optimizer
typedef IMP::base::Vector < IMP::base::WeakPointer < Optimizer > >	OptimizersTemp

Detailed Description

Algorithm is as per Shanno and Phua, ACM Transactions On Mathematical Software 6 (December 1980), 618-622

Conjugate gradients optimization is sensitive to the scales of the derivatives of the various attributes being optimized. By default, the scales are estimated from the range of values found for the attribute upon initialization. These estimates can be viewed either by calling Model::get_range(my_float_key) or by turning on TERSE logging and looking at logged messages. If this estimate does not accurately reflect the scale, then you can use Model::set_range to set a more accurate range for the parameters.

Definition at line 32 of file core/ConjugateGradients.h.

The documentation for this class was generated from the following file:

core/ConjugateGradients.h

Public Member Functions

Additional Inherited Members

Detailed Description